AI Engineer at Amazon | Agentic AI | Multi-Agent Orchestration | LLM | RAG | Python
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Amazon
Frontend Developer
June 20, 2026 – Present
invoice-parser
April 24, 2026 – Present
AI-powered invoice extraction — AWS Bedrock + Strands Agents, mandatory worker verification, RLHF feedback loop
View Projectmemory-agent
April 12, 2026 – Present
AI agent that never forgets — LangGraph + Claude + persistent memory. 3 memory types, proof report included.
View Projectcareer-agent
April 6, 2026 – Present
AI-powered LinkedIn job search automation — auto-apply, lead finder, daily posts, job scoring
View Projectrag-pipeline-eval
March 24, 2026 – Present
LangChain + FAISS + Bedrock RAG system with automated RAGAS quality scoring
View Projectmulti-agent-task-planner
March 24, 2026 – Present
LangGraph + AWS Bedrock multi-agent system with 4 specialized AI agents for goal decomposition and execution planning
View Projectllm-prompt-optimizer
March 24, 2026 – Present
Automated prompt testing framework - evaluates variants on accuracy, token usage, cost
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards AI/ML and backend development, with limited explicit frontend-focused projects. While there are projects using JavaScript, CSS, HTML, and TypeScript, the descriptions do not detail complex frontend challenges or design patterns. This suggests a potential mismatch with a dedicated 'Frontend Developer' role, as the primary interest and demonstrated depth appear to be in AI/ML and Python. The candidate's current role at Amazon as a 'Frontend Developer' is listed as starting in the future (2026), so it cannot be used to assess current cultural fit or experience.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a proactive and self-directed approach to learning and development, particularly in AI/ML.